The invention discloses a solar flare forecasting method based on a convolutional neural network model, and the method comprises the steps: A, preparing observation raw data of an active region; B, building a depth forecasting model, extracting features from the observation data through employing a convolutional neural network, and forecasting whether the active region generates solar flare or not. The method can directly enable the observation raw data to serve as the input of the model, automatically extract a forecasting factor for the forecasting of the solar flare from the raw data through employing the strong learning capability of a depth neural network, builds a corresponding forecasting model, and achieves an ideal forecasting capability through the forecasting model.